Whom We Trust, What We Fear: COVID-19 Fear and the Politics of Information

TL;DR

This study investigates how information sources shape fear during COVID-19 using Delphi US CTIS data collected from May 2021 to June 2022. It employs correlation analyses and a DoWhy-based causal framework to compare the influence of information sources, age, and education on self-reported fear, and then uses clustering to relate state patterns of information-source use to political orientation. The findings show that information sources are the dominant driver of fear, with credible sources sometimes mitigating fear and other sources amplifying it, and that fear and source usage rise and fall with infection trends. The work highlights the information ecosystem's role in emotional responses during crises and reveals a strong link between information patterns and political geography, underscoring implications for public health communication and democratic trust.

Abstract

The COVID-19 pandemic triggered not only a global health crisis but also an infodemic, an overload of information from diverse sources influencing public perception and emotional responses. In this context, fear emerged as a central emotional reaction, shaped by both media exposure and demographic factors. In this study, we analyzed the relationship between individuals' self-reported levels of fear about COVID-19 and the information sources they rely on, across nine source categories, including medical experts, government institutions, media, and personal networks. In particular, we defined a score that ranks fear levels based on self-reported concerns about the pandemic, collected through the Delphi CTIS survey in the United States between May 2021 and June 2022. We found that both fear levels and information source usage closely follow COVID-19 infection trends, exhibit strong correlations within each group (fear levels across sources are strongly correlated, as are patterns of source usage), and vary significantly across demographic groups, particularly by age and education. Applying causal inference methods, we found that among age, education, and information source, the latter is the most influential factor affecting individuals' fear levels. We further quantified the impact of different information sources on fear by estimating the average treatment effect, indicating how each source alters fear relative to a control. Furthermore, we demonstrated that information source preferences can reliably match the political orientation of U.S. states. These findings highlight the importance of information ecosystem dynamics in shaping emotional and behavioral responses during large-scale crises.

Figures (13)

• Figure 1: Schematic representation of our study.
• Figure 2: Causal inference model used.
• Figure 3: Temporal evolution of $\phi_{s'}$ for each of the nine singleton information sources---values on the left axis---, alongside the official infection counts in the U.S.---values on the right axis---between May 2021 and June 2022. To reduce noise, official infections and $\phi_{s'}$ were smoothed using a two-month rolling average.
• Figure 4: Spearman correlation coefficients among the time series shown in Figure \ref{['fig:fearsourceI']}.
• Figure 5: Boxplots showing the distribution of $\phi_{s'}$ across the nine singleton information sources, stratified by a)Age---where $Age_1$, $Age_2$, and $Age_3$ refers to the three Age groups---and b)Education groups---where $Edu_1$, $Edu_2$, and $Edu_3$ refers to the three Education groups.